{"id":"W4414797459","doi":"10.1088/2632-2153/ae0f38","title":"HPGe-Compton Net: a physics-guided CNN for fast gamma spectra analysis via Compton region learning","year":2025,"lang":"en","type":"article","venue":"Machine Learning Science and Technology","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Mitacs","keywords":"Detector; Convolutional neural network; Semiconductor detector; Data set; Compton scattering; Feature (linguistics); Gamma spectroscopy; Artificial neural network; Radioactive waste","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002785293,0.0001892757,0.0003205688,0.0005404362,0.001122896,0.0001326941,0.0004727355,0.00005916342,0.00002450633],"category_scores_gemma":[0.00003400374,0.0001839282,0.0001037486,0.003660826,0.0005198331,0.0001318728,0.0002578286,0.0004863491,0.00001241446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000374317,"about_ca_system_score_gemma":0.00006883167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002414507,"about_ca_topic_score_gemma":0.000006765842,"domain_scores_codex":[0.9985952,0.00002386425,0.0002202966,0.0005856616,0.0001594655,0.0004155096],"domain_scores_gemma":[0.9991664,0.00006105379,0.0001681791,0.0003539292,0.0001947446,0.00005567927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000108503,0.0001473756,0.2051846,0.0000172003,0.0002266857,7.138651e-7,0.0001754909,0.003411429,0.0290491,0.412193,0.0002524944,0.349331],"study_design_scores_gemma":[0.001160032,0.0002600173,0.01077808,0.00004496186,0.0004557335,0.000003194721,0.000663995,0.7578405,0.01517843,0.1656891,0.04730561,0.0006202955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4765004,0.00007730301,0.5051717,0.005230515,0.00007303794,0.0004686141,0.000006291703,0.0003387952,0.0121334],"genre_scores_gemma":[0.9970704,0.000005215059,0.001601834,0.00005326242,0.00007812506,0.00005883477,0.00003459262,0.00001461793,0.001083123],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7544291,"threshold_uncertainty_score":0.8636521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007277837883385999,"score_gpt":0.2664585059010178,"score_spread":0.2591806680176318,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}